mirror of
https://gitee.com/dify_ai/dify.git
synced 2024-12-04 20:28:12 +08:00
106 lines
4.0 KiB
Python
106 lines
4.0 KiB
Python
import logging
|
|
import time
|
|
|
|
import click
|
|
from celery import shared_task
|
|
|
|
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
|
|
from extensions.ext_database import db
|
|
from extensions.ext_storage import storage
|
|
from models.dataset import (
|
|
AppDatasetJoin,
|
|
Dataset,
|
|
DatasetProcessRule,
|
|
DatasetQuery,
|
|
Document,
|
|
DocumentSegment,
|
|
)
|
|
from models.model import UploadFile
|
|
|
|
|
|
# Add import statement for ValueError
|
|
@shared_task(queue="dataset")
|
|
def clean_dataset_task(
|
|
dataset_id: str,
|
|
tenant_id: str,
|
|
indexing_technique: str,
|
|
index_struct: str,
|
|
collection_binding_id: str,
|
|
doc_form: str,
|
|
):
|
|
"""
|
|
Clean dataset when dataset deleted.
|
|
:param dataset_id: dataset id
|
|
:param tenant_id: tenant id
|
|
:param indexing_technique: indexing technique
|
|
:param index_struct: index struct dict
|
|
:param collection_binding_id: collection binding id
|
|
:param doc_form: dataset form
|
|
|
|
Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct)
|
|
"""
|
|
logging.info(click.style("Start clean dataset when dataset deleted: {}".format(dataset_id), fg="green"))
|
|
start_at = time.perf_counter()
|
|
|
|
try:
|
|
dataset = Dataset(
|
|
id=dataset_id,
|
|
tenant_id=tenant_id,
|
|
indexing_technique=indexing_technique,
|
|
index_struct=index_struct,
|
|
collection_binding_id=collection_binding_id,
|
|
)
|
|
documents = db.session.query(Document).filter(Document.dataset_id == dataset_id).all()
|
|
segments = db.session.query(DocumentSegment).filter(DocumentSegment.dataset_id == dataset_id).all()
|
|
|
|
if documents is None or len(documents) == 0:
|
|
logging.info(click.style("No documents found for dataset: {}".format(dataset_id), fg="green"))
|
|
else:
|
|
logging.info(click.style("Cleaning documents for dataset: {}".format(dataset_id), fg="green"))
|
|
# Specify the index type before initializing the index processor
|
|
if doc_form is None:
|
|
raise ValueError("Index type must be specified.")
|
|
index_processor = IndexProcessorFactory(doc_form).init_index_processor()
|
|
index_processor.clean(dataset, None)
|
|
|
|
for document in documents:
|
|
db.session.delete(document)
|
|
|
|
for segment in segments:
|
|
db.session.delete(segment)
|
|
|
|
db.session.query(DatasetProcessRule).filter(DatasetProcessRule.dataset_id == dataset_id).delete()
|
|
db.session.query(DatasetQuery).filter(DatasetQuery.dataset_id == dataset_id).delete()
|
|
db.session.query(AppDatasetJoin).filter(AppDatasetJoin.dataset_id == dataset_id).delete()
|
|
|
|
# delete files
|
|
if documents:
|
|
for document in documents:
|
|
try:
|
|
if document.data_source_type == "upload_file":
|
|
if document.data_source_info:
|
|
data_source_info = document.data_source_info_dict
|
|
if data_source_info and "upload_file_id" in data_source_info:
|
|
file_id = data_source_info["upload_file_id"]
|
|
file = (
|
|
db.session.query(UploadFile)
|
|
.filter(UploadFile.tenant_id == document.tenant_id, UploadFile.id == file_id)
|
|
.first()
|
|
)
|
|
if not file:
|
|
continue
|
|
storage.delete(file.key)
|
|
db.session.delete(file)
|
|
except Exception:
|
|
continue
|
|
|
|
db.session.commit()
|
|
end_at = time.perf_counter()
|
|
logging.info(
|
|
click.style(
|
|
"Cleaned dataset when dataset deleted: {} latency: {}".format(dataset_id, end_at - start_at), fg="green"
|
|
)
|
|
)
|
|
except Exception:
|
|
logging.exception("Cleaned dataset when dataset deleted failed")
|